Normalising OLAP cubes for controlling sparsity

Authors:
Tapio Niemi;Jyrki Nummenmaa;Peter Thanisch
Affiliations:
Department of Computer and Information Sciences, University of Tampere, FIN-33014, Tampere, Finland;Department of Computer and Information Sciences, University of Tampere, FIN-33014, Tampere, Finland;IBM, St. Andrew Square, Edinburgh, Scotland, UK
Venue:
Data & Knowledge Engineering
Year:
2003

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Abstract

A poorly designed OLAP (on-line analytical processing) cube can have a size much larger than the volume of information, potentially leading to problems with performance and usability. We give a new normal form for OLAP cube design and synthesis and decomposition algorithms to produce normalised OLAP cube schemata. OLAP cube normalisation controls the structural sparsity resulting from inter-dimensional functional dependencies. We assume that functional dependencies are used to describe the constraints of the application universe of discourse. Our methods help the user to identify cube schemata with structural sparsity, and to change the design in order to obtain more economy of space.